The Extent and Impact of Variation in ADME Genes in Sub-Saharan African Populations

Characterization of CYP2B6 and CYP2A6 Pharmacogenetic Variation in Sub-Saharan African Populations

Genetic variation in CYP2B6 and CYP2A6 is known to impact interindividual response to antiretrovirals, nicotine, and bupropion, among other drugs. However, the full catalogue of clinically relevant pharmacogenetic variants in these genes is yet to be established, especially across African populations. This study therefore aimed to characterize the star allele (haplotype) distribution in CYP2B6 and CYP2A6 across diverse and understudied sub-Saharan African (SSA) populations. We called star alleles from 961 high-depth full genomes using StellarPGx, Aldy, and PyPGx. In addition, we performed CYP2B6 and CYP2A6 star allele frequency comparisons between SSA and other global biogeographical groups represented in the new 1000 Genomes Project high-coverage dataset (n = 2,000). This study presents frequency information for star alleles in CYP2B6 (e.g., *6 and *18; frequency of 21-47% and 2-19%, respectively) and CYP2A6 (e.g., *4, *9, and *17; frequency of 0-6%, 3-10%, and 6-20%, respectively), and predicted phenotypes (for CYP2B6), across various African populations. In addition, 50 potentially novel African-ancestry star alleles were computationally predicted by StellarPGx in CYP2B6 and CYP2A6 combined. For each of these genes, over 4% of the study participants had predicted novel star alleles. Three novel star alleles in CYP2A6 (*54, *55, and *56) and CYP2B6 apiece, and several suballeles were further validated via targeted Single-Molecule Real-Time resequencing. Our findings are important for informing the design of comprehensive pharmacogenetic testing platforms, and are highly relevant for personalized medicine strategies, especially relating to antiretroviral medication and smoking cessation treatment in Africa and the African diaspora. More broadly, this study highlights the importance of sampling diverse African ethnolinguistic groups for accurate characterization of the pharmacogene variation landscape across the continent.

The Case for Pre-Emptive Pharmacogenetic Screening in South Africa

Lack of equitable representation of global genetic diversity has hampered the implementation of genomic medicine in under-represented populations, including those on the African continent. Data from the multi-national Pre-emptive Pharmacogenomic Testing for Preventing Adverse Drug Reactions (PREPARE) study suggest that genotype guidance for prescriptions reduced the incidence of clinically relevant adverse drug reactions (ADRs) by 30%. In this study, hospital dispensary trends from a tertiary South African (SA) hospital (Steve Biko Academic Hospital; SBAH) were compared with the drugs monitored in the PREPARE study. Dispensary data on 29 drugs from the PREPARE study accounted for ~10% of total prescriptions and ~9% of the total expenditure at SBAH. VigiLyze data from the South African Health Products Regulatory Authority were interrogated for local ADRs related to these drugs; 27 were listed as being suspected, concomitant, or interacting in ADR reports. Furthermore, a comparison of pharmacogene allele frequencies between African and European populations was used to frame the potential impact of pre-emptive pharmacogenetic screening in SA. Enumerating the benefit of pre-emptive pharmacogenetic screening in SA will only be possible once we initiate its full application. However, regional genomic diversity, disease burden, and first-line treatment options could be harnessed to target stratified PGx today.

The African Liver Tissue Biorepository Consortium: Capacitating Population-Appropriate Drug Metabolism, Pharmacokinetics, and Pharmacogenetics Research in Drug Discovery and Development

Pharmaceutical companies subject all new molecular entities to a series of in vitro metabolic characterizations that guide the selection and/or design of compounds predicted to have favorable pharmacokinetic properties in humans. Current drug metabolism research is based on liver tissue predominantly obtained from people of European origin, with limited access to tissue from people of African origin. Given the interindividual and interpopulation genomic variability in genes encoding drug-metabolizing enzymes, efficacy and safety of some drugs are poorly predicted for African populations. To address this gap, we have established the first comprehensive liver tissue biorepository inclusive of people of African origin. The African Liver Tissue Biorepository Consortium currently includes three institutions in South Africa and one in Zimbabwe, with plans to expand to other African countries. The program has collected 67 liver samples as of July 2023. DNA from the donors was genotyped for 120 variants in 46 pharmacogenes and revealed variants that are uniquely found in African populations, including the low-activity, African-specific CYP2C9*5 and *8 variants relevant to the metabolism of diclofenac. Larger liver tissue samples were used to isolate primary human hepatocytes. Viability of the hepatocytes and microsomal fractions was demonstrated by the activity of selected cytochrome P450s. This resource will be used to ensure the safety and efficacy of existing and new drugs in African populations. This will be done by characterizing compounds for properties such as drug clearance, metabolite and enzyme identification, and drug-drug and drug-gene interactions. SIGNIFICANCE STATEMENT: Standard optimization of the drug metabolism of new molecular entities in the pharmaceutical industry uses subcellular fractions such as microsomes and isolated primary hepatocytes, being done mainly with tissue from donors of European origin. Pharmacogenetics research has shown that variants in genes coding for drug-metabolizing enzymes have interindividual and interpopulation differences. We established an African liver tissue biorepository that will be useful in ensuring drug discovery and development research takes into account drug responses in people of African origin.

Characterization of CYP2C19 pharmacogenetic variation in African populations and comparison with other global populations

Background: CYP2C19 is important in the metabolism of clopidogrel and several antidepressants. This study aimed to characterize the distribution of CYP2C19 star alleles (haplotypes) across diverse African populations compared with global populations. Methods: CYP2C19 star alleles and diplotypes were called from high coverage genomes using the StellarPGx pipeline. Results: CYP2C19*1 (51%), *2 (17%) and *17 (22%) were the most common star alleles across African populations in this study. It was observed that 3% of African participants had potentially novel CYP2C19 haplotypes. Conclusion: This study supports the necessity for CYP2C19 pharmacogenetic testing in African and global clinical settings, as well as the importance of comprehensive star allele characterization in the African context.

Pharmacogenetics of 6-mercaptopurine in a black Zimbabwean cohort treated for acute lymphoblastic leukaemia

Background: 6-mercaptopurine usage is associated with myelotoxicity and increased risk in patients carrying metabolism-related genetic variations. This study aimed to determine the frequency of candidate gene polymorphisms and their association with 6-mercaptopurine intolerance. Methods: A total of 41 patients on acute lymphoblastic leukaemia treatment were genotyped for TPMT and NUDT15 (rs116855232) alleles, and their association with dose intensity was analyzed. Results: The defective TPMT*3C allele frequency was 9.8%. The median maintenance dose intensity for TPMT*1/*3C participants was considerably lower (47%) when compared with the TPMT*1/*1 wild-type (77%), although not statistically significant. Conclusion: This is the first pharmacogenetics study carried out in a black Zimbabwean leukemia patient cohort. The high defective TPMT*3C (9.8%) allele frequency points to the potential utility of pharmacogenetics testing for safe usage of 6-mercaptopurine in this population.

Characterization of CYP2D6 Pharmacogenetic Variation in Sub-Saharan African Populations

Cytochrome P450 2D6 (CYP2D6) is a key enzyme in drug response owing to its involvement in the metabolism of ~ 25% of clinically prescribed medications. The encoding CYP2D6 gene is highly polymorphic, and many pharmacogenetics studies have been performed worldwide to investigate the distribution of CYP2D6 star alleles (haplotypes); however, African populations have been relatively understudied to date. In this study, the distributions of CYP2D6 star alleles and predicted drug metabolizer phenotypes-derived from activity scores-were examined across multiple sub-Saharan African populations based on bioinformatics analysis of 961 high-depth whole genome sequences. This was followed by characterization of novel star alleles and suballeles in a subset of the participants via targeted high-fidelity Single-Molecule Real-Time resequencing (Pacific Biosciences). This study revealed varying frequencies of known CYP2D6 alleles and predicted phenotypes across different African ethnolinguistic groups. Twenty-seven novel CYP2D6 star alleles were predicted computationally and two of them were further validated. This study highlights the importance of studying variation in key pharmacogenes such as CYP2D6 in the African context to better understand population-specific allele frequencies. This will aid in the development of better genotyping panels and star allele detection approaches with a view toward supporting effective implementation of precision medicine strategies in Africa and across the African diaspora.

Characterization of ADME Gene Variation in Colombian Population by Exome Sequencing

In genes related to drug pharmacokinetics, molecular variations determine interindividual variability in the therapeutic efficacy and adverse drug reactions. The assessment of single-nucleotide variants (SNVs) is used with growing frequency in pharmacogenetic practice, and recently, high-throughput genomic analyses obtained through next-generation sequencing (NGS) have been recognized as powerful tools to identify common, rare and novel variants. These genetic profiles remain underexplored in Latin-American populations, including Colombia. In this study, we investigated the variability of 35 genes included in the ADME core panel (absorption, distribution, metabolism, and excretion) by whole-exome sequencing (WES) of 509 unrelated Colombian individuals with no previous reports of adverse drug reactions. Rare variants were filtered according to the minor allele frequencies (MAF) <1% and potential deleterious consequences. The functional impact of novel and rare missense variants was assessed using an optimized framework for pharmacogenetic variants. Bioinformatic analyses included the identification of clinically validated variants described in PharmGKB and ClinVar databases. Ancestry from WES data was inferred using the R package EthSEQ v2.1.4. Allelic frequencies were compared to other populations reported in the public gnomAD database. Our analysis revealed that rare missense pharmacogenetic variants were 2.1 times more frequent than common variants with 121 variants predicted as potentially deleterious. Rare loss of function (LoF) variants were identified in 65.7% of evaluated genes. Regarding variants with clinical pharmacogenetic effect, our study revealed 89 sequence variations in 28 genes represented by missense (62%), synonymous (22.5%), splice site (11.2%), and indels (3.4%). In this group, ABCB1, ABCC2, CY2B6, CYP2D6, DPYD, NAT2, SLC22A1, and UGTB2B7, are the most polymorphic genes. NAT2, CYP2B6 and DPYD metabolizer phenotypes demonstrated the highest variability. Ancestry analysis indicated admixture in 73% of the population. Allelic frequencies exhibit significant differences with other Latin-American populations, highlighting the importance of pharmacogenomic studies in populations of different ethnicities. Altogether, our data revealed that rare variants are an important source of variability in pharmacogenes involved in the pharmacokinetics of drugs and likely account for the unexplained interindividual variability in drug response. These findings provide evidence of the utility of WES for pharmacogenomic testing and into clinical practice.

SWAAT Bioinformatics Workflow for Protein Structure-Based Annotation of ADME Gene Variants

Recent genomic studies have revealed the critical impact of genetic diversity within small population groups in determining the way individuals respond to drugs. One of the biggest challenges is to accurately predict the effect of single nucleotide variants and to get the relevant information that allows for a better functional interpretation of genetic data. Different conformational scenarios upon the changing in amino acid sequences of pharmacologically important proteins might impact their stability and plasticity, which in turn might alter the interaction with the drug. Current sequence-based annotation methods have limited power to access this type of information. Motivated by these calls, we have developed the Structural Workflow for Annotating ADME Targets (SWAAT) that allows for the prediction of the variant effect based on structural properties. SWAAT annotates a panel of 36 ADME genes including 22 out of the 23 clinically important members identified by the PharmVar consortium. The workflow consists of a set of Python codes of which the execution is managed within Nextflow to annotate coding variants based on 37 criteria. SWAAT also includes an auxiliary workflow allowing a versatile use for genes other than ADME members. Our tool also includes a machine learning random forest binary classifier that showed an accuracy of 73%. Moreover, SWAAT outperformed six commonly used sequence-based variant prediction tools (PROVEAN, SIFT, PolyPhen-2, CADD, MetaSVM, and FATHMM) in terms of sensitivity and has comparable specificity. SWAAT is available as an open-source tool.

African Genomic Medicine Portal: A Web Portal for Biomedical Applications

Genomics data are currently being produced at unprecedented rates, resulting in increased knowledge discovery and submission to public data repositories. Despite these advances, genomic information on African-ancestry populations remains significantly low compared with European- and Asian-ancestry populations. This information is typically segmented across several different biomedical data repositories, which often lack sufficient fine-grained structure and annotation to account for the diversity of African populations, leading to many challenges related to the retrieval, representation and findability of such information. To overcome these challenges, we developed the African Genomic Medicine Portal (AGMP), a database that contains metadata on genomic medicine studies conducted on African-ancestry populations. The metadata is curated from two public databases related to genomic medicine, PharmGKB and DisGeNET. The metadata retrieved from these source databases were limited to genomic variants that were associated with disease aetiology or treatment in the context of African-ancestry populations. Over 2000 variants relevant to populations of African ancestry were retrieved. Subsequently, domain experts curated and annotated additional information associated with the studies that reported the variants, including geographical origin, ethnolinguistic group, level of association significance and other relevant study information, such as study design and sample size, where available. The AGMP functions as a dedicated resource through which to access African-specific information on genomics as applied to health research, through querying variants, genes, diseases and drugs. The portal and its corresponding technical documentation, implementation code and content are publicly available.

Clinical Trial Diversity: An Opportunity for Improved Insight into the Determinants of Variability in Drug Response

Although the number of countries participating in pivotal trials submitted to enable drug registration has nearly doubled over the past 25 years, there has not been a substantial increase in the diversity of clinical trial populations. In parallel, our understanding of factors that influence medicine response and variability has continued to evolve. The notion of intrinsic and extrinsic sources of variability has been embedded into different regulatory guidelines, including the recent guideline on the importance of enhancing the diversity of clinical trial populations.

In addition to presenting the clinical and scientific reasons for ensuring that clinical trial populations represent the demographics of patient populations, this overview outlines the efforts of regulatory agencies, patient advocacy groups and clinical researchers to attain this goal through strategies to meet representation in recruitment targets and broaden eligibility criteria. Despite these efforts, challenges to participation in clinical trials remain, and certain groups continue to be underrepresented in development programmes. These challenges are amplified when the representativeness of specific groups may vary across countries and regions in a global clinical programme.

Whilst enhanced trial diversity is a critical step towards ensuring that results will be representative of patient populations, a concerted effort is required to characterise further the factors influencing interindividual and regional differences in response for global populations. Quantitative clinical pharmacology principles should be applied to allow extrapolation of data across groups or regions as well as provide insight into the effect of patient‐specific characteristics on a medicine's dose rationale and efficacy and safety profiles.

Single Nucleotide Polymorphism Induces Divergent Dynamic Patterns in CYP3A5: A Microsecond Scale Biomolecular Simulation of Variants Identified in Sub-Saharan African Populations

Pharmacogenomics aims to reveal variants associated with drug response phenotypes. Genes whose roles involve the absorption, distribution, metabolism, and excretion of drugs, are highly polymorphic between populations. High coverage whole genome sequencing showed that a large proportion of the variants for these genes are rare in African populations. This study investigated the impact of such variants on protein structure to assess their functional importance. We used genetic data of CYP3A5 from 458 individuals from sub-Saharan Africa to conduct a structural bioinformatics analysis. Five missense variants were modeled and microsecond scale molecular dynamics simulations were conducted for each, as well as for the CYP3A5 wildtype and the Y53C variant, which has a known deleterious impact on enzyme activity. The binding of ritonavir and artemether to CYP3A5 variant structures was also evaluated. Our results showed different conformational characteristics between all the variants. No significant structural changes were noticed. However, the genetic variability seemed to act on the plasticity of the protein. The impact on drug binding might be drug dependant. We concluded that rare variants hold relevance in determining the pharmacogenomics properties of populations. This could have a significant impact on precision medicine applications in sub-Saharan Africa.